Johnson Dayna A, Brown Devin L, Morgenstern Lewis B, Meurer William J, Lisabeth Lynda D
Division of Sleep and Circadian Disorders, Brigham and Women's Hospital and Harvard Medical School, 221 Longwood Ave BLI 225, Boston, MA 02115, USA; Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights 2649B SPH 1, Ann Arbor, MI 48109, USA.
Department of Neurology, University of Michigan, 1920 Taubman Center, Ann Arbor, MI 48109, USA; Stroke Program, University of Michigan, 1500 E Medical Center Dr CVC 3393, Ann Arbor, MI 48109, USA.
Sleep Health. 2015 Sep;1(3):148-155. doi: 10.1016/j.sleh.2015.06.002. Epub 2015 Aug 10.
Neighborhood characteristics have been linked to health outcomes. Various mechanisms link neighborhoods and health outcomes; sleep patterns may be 1 contributor; however, little is known about the social determinants of disordered sleep. We examined the association of neighborhood characteristics with sleep duration and daytime sleepiness.
Participants (n = 801) enrolled as pairs (55 without pair), from 10 churches in the Stroke Health and Risk Education project; 760 were included for analysis (41 withdrew). Sleep duration (hours of sleep at night) and daytime sleepiness (adaptation of Berlin questionnaire; range, 0-3 [more daytime sleepiness]) were self-reported. Neighborhood characteristics included disadvantage, per capita violent crime (census tract level), and safety (self-reported and individual level). We fit generalized linear mixed models and multinomial and binomial logistic regression models to examine the associations between neighborhood characteristics and sleep outcomes while accounting for the clustering within churches and pairs, before and after adjustment for self-reported confounders (age, gender, income, education, body mass index, depressive symptoms, hypertension, and diabetes).
The mean hours of sleep duration is 6.7 ± 1.2, and the mean daytime sleepiness is 0.8 ± 0.9. Neighborhood characteristics were not associated with sleep duration. Higher perceived neighborhood safety was associated with an 18.4% lower odds of daytime sleepiness in the unadjusted model (odds ratio, 0.82 [95% confidence interval, 0.69-0.96]). The association was attenuated in the fully adjusted model. Neighborhood disadvantage and violent crime were related to lower daytime sleepiness; however, associations were not statistically significant.
Self-reported neighborhood safety was associated with lower daytime sleepiness. Future exploration of the pathways linking neighborhood characteristics and sleep is warranted.
社区特征与健康结果相关。多种机制将社区与健康结果联系起来；睡眠模式可能是其中一个因素；然而，关于睡眠障碍的社会决定因素知之甚少。我们研究了社区特征与睡眠时间和日间嗜睡之间的关联。
参与者（n = 801）以成对形式（55人无配对）从卒中健康与风险教育项目的10所教堂招募；760人纳入分析（41人退出）。睡眠时间（夜间睡眠时间）和日间嗜睡情况（采用柏林问卷改编版；范围为0 - 3[日间嗜睡程度更高]）通过自我报告获得。社区特征包括劣势、人均暴力犯罪（普查区层面）和安全性（自我报告的个人层面）。我们拟合了广义线性混合模型以及多项和二项逻辑回归模型，以研究社区特征与睡眠结果之间的关联，同时考虑教堂和配对中的聚类情况，在对自我报告的混杂因素（年龄、性别、收入、教育程度、体重指数、抑郁症状、高血压和糖尿病）进行调整前后。
平均睡眠时间为6.7±1.2小时，平均日间嗜睡评分为0.8±0.9。社区特征与睡眠时间无关。在未调整模型中，更高的社区安全感与日间嗜睡几率降低18.4%相关（优势比，0.82[95%置信区间，0.69 - 0.96]）。在完全调整模型中，这种关联减弱。社区劣势和暴力犯罪与较低的日间嗜睡相关；然而，关联无统计学意义。
自我报告的社区安全感与较低的日间嗜睡相关。未来有必要探索连接社区特征与睡眠的途径。
